South Korean memory chipmaker SK hynix has announced a mid- to long-term investment plan worth 1,100 trillion South Korean won (~$713 billion) to expand its manufacturing capacity in South Korea. To help fund the expansion, the company plans to list on the Nasdaq exchange in the U.S.
As SK hynix begins shipping its next-generation memory products, financial markets are considering what might happen if the current pace of AI infrastructure spending slows.
Expanding domestic manufacturing
To meet the demand for advanced memory solutions, SK hynix has formalized a multiphase expansion strategy across three primary geographic clusters in South Korea.
SK hynix said it will invest KRW 600 trillion (~$390 billion) in the Yongin semiconductor cluster. The company now plans to complete construction of a fourth fab there by 2033, 12 years earlier than originally planned.
View All Additionally, the company said it will allocate KRW 100 trillion (~$65 billion) in Cheongju to build new NAND fabs, install production equipment, and expand packaging capabilities needed for high-bandwidth memory (HBM). The company will also invest KRW 400 trillion (~$260 billion) in the Southwestern region in several phases.
SK hynix president and CEO Kwak Noh-Jung addressed the rationale for the geographic expansion during a national briefing on advanced industries. “The AI industry has moved beyond the training phase and entered an era in which AI services are being deployed at scale,” he stated, noting that the Yongin site alone would not satisfy future market needs. Kwak further emphasized that current supply constraints and rising demand make expanding production capacity essential for the company.
“SK hynix will invest a total of KRW 100 trillion in Cheongju—KRW 80 trillion in the M17 NAND production fab and KRW 20 trillion in the P&T7 advanced packaging facility,” Kwak said. “We will re-establish Cheongju as a key hub for driving the competitiveness of the memory semiconductor industry in Korea.”
SK Group also plans to support these facilities by building 15 gigawatts of AI data center infrastructure throughout South Korea.
Transition to next-generation HBM
HBM is important for AI data processing, but it produces fewer usable chips per wafer than conventional DRAM. HBM uses through-silicon vias to connect stacked chips, increasing chip size. As HBM becomes a bigger part of production, much more wafer manufacturing capacity is needed.
SK hynix is advancing its product development and has recently shipped 12-layer HBM4E memory samples to major customers. These new memory modules can process data at up to 16 gigabits per second per pin and are 20% more power efficient than earlier versions.
The manufacturing process uses the company’s proprietary Advanced Mass Reflow Molded Underfill technology, which it says increases the memory chips’ heat resistance by 17%. This helps them run reliably in high-performance computing (HPC) settings.
Ahn Hyun, president and chief development officer at SK hynix, commented on the product delivery. “SK hynix has laid the foundation to strengthen its AI leadership with HBM4E based on its market-leading technological capabilities and manufacturing expertise,” Hyun said. He added that the company is collaborating closely with its partners to bring the product into mass production.
Securing capital through U.S. listing
To fund its 1,100 trillion won plan in South Korea, the company said it will draw on various sources of capital. It plans to deploy the investment in phases, depending on market demand and cash flow.
SK hynix plans to strengthen its finances by listing American depositary receipts on the Nasdaq Global Select Exchange on July 10. The company aims to raise 45.45 trillion won (~$29 billion), well above the $10 billion previously estimated by South Korean media.
The planned Nasdaq listing will affect competition in the global memory market. SK hynix said it plans to use the proceeds to build fabs, buy machinery, and get equipment. Analysts say that by increasing chip supply with this capital, SK hynix could boost its position by lowering some component prices.
Listing SK hynix shares in the U.S. will give both institutional and retail investors another way to invest in the memory chip sector. This could prompt some investors to move money away from other options, such as Micron.
Navigating the risk of a spending contraction
The semiconductor industry’s growth relies on hyperscalers continuing to spend heavily on data centers.
Nomura Securities predicts that global investment in AI data centers will rise from $466 billion in 2025 to $3.379 trillion by 2030, with an annual growth rate of about 48%. This growth is bringing high profits to memory makers, but some economists warn of excessive investment in the sector.
A recent annual report from the Bank for International Settlements (BIS), a group of global central banks based in Switzerland, described the big-picture risks linked to current tech spending levels.
The report warned that if AI tools do not deliver enough financial returns to cover their high upfront costs, spending could suddenly drop. This could then cause major problems for the global financial system.
BIS also noted that these risks go beyond just the tech sector. If tech companies cut spending, it would quickly affect construction companies and other supply chain companies.
The report also said that debt used to pay for data centers could lead to more companies defaulting. At the same time, high inflation would make it harder for central banks to help if the economy runs into trouble.
SK hynix said it expects demand for advanced computing hardware to stay strong for long enough to justify expanding its manufacturing capacity
See also:
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[SK hynix Receives 2026 IEEE Corporate Innovation Award](https://www.eetimes.com/sk-hynix-receives-2026-ieee-corporate-innovation-award/)
[LPDDR6 Roadmap Leads to the Data Center](https://www.eetimes.com/lpddr6-roadmap-leads-to-the-data-center/)
[Gartner Says Supply Chain Confronts Geopolitical and AI Challenges](https://www.eetimes.com/gartner-says-supply-chain-confront-geopolitical-and-ai-challenges/)